Beyond the hype, homomorphic encryption’s potential for secure classified inference is promising yet faces real-world challenges worth exploring.
Browsing Tag
data privacy
14 posts
Consent at Scale: Can Intelligence Ever Be Truly Informed?
Lurking behind complex data systems, true informed consent at scale remains elusive, leaving us to question if genuine understanding is ever possible.
Data Retention and Deletion: Drawing the Line
Just understanding data retention and deletion is only the beginning; discovering how to draw the line effectively can protect your organization from risks.
Cross-Border Data Rules: The Legal Minefield for AI
Struggling with cross-border data rules? Discover essential strategies to navigate complex legal landscapes and protect your AI operations worldwide.
Federated Learning for Sensitive Missions: How It Works
Federated Learning for Sensitive Missions: How It Works explains how this innovative approach maintains data privacy while enabling collaborative AI model training.
Covert Channels in ML Pipelines: Hidden Signals 101
Keen understanding of covert channels in ML pipelines reveals how hidden signals can compromise security—continue reading to uncover detection strategies.
Anonymization vs. Pseudonymization: What’s Safe Enough?
Just understanding the differences between anonymization and pseudonymization can help you decide which privacy measure is truly safe enough for your data needs.
SIGINT, HUMINT, OSINT: Where AI Helps—and Hurts
Lifting the veil on AI’s role in SIGINT, HUMINT, and OSINT reveals powerful tools and serious pitfalls that demand careful consideration.
RAG Security: Keeping Retrieval-Augmented Models From Going Rogue
For effective RAG security, focus on strict controls and vigilant monitoring to prevent models from going rogue—discover how to safeguard your system.
Fine-Tuning Leaks: When Custom Models Spill Secrets
A deep dive into how fine-tuning custom models can inadvertently expose sensitive secrets and what steps to take to prevent leaks.